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@article{1699116,
author = {Jandová, Marie and Daňko, Marek and Urbanová, Petra},
article_location = {Clare},
article_number = {January},
doi = {http://dx.doi.org/10.1016/j.forsciint.2020.110612},
keywords = {age verification; age estimation; 3D facial models; random forests; FIDENTIS Database},
language = {eng},
issn = {0379-0738},
journal = {Forensic Science International},
title = {Age verification using random forests on facial 3D landmarks},
url = {https://doi.org/10.1016/j.forsciint.2020.110612},
volume = {318},
year = {2021}
}
TY - JOUR
ID - 1699116
AU - Jandová, Marie - Daňko, Marek - Urbanová, Petra
PY - 2021
TI - Age verification using random forests on facial 3D landmarks
JF - Forensic Science International
VL - 318
IS - January
SP - 1-10
EP - 1-10
PB - Elsevier Ireland Ltd
SN - 03790738
KW - age verification
KW - age estimation
KW - 3D facial models
KW - random forests
KW - FIDENTIS Database
UR - https://doi.org/10.1016/j.forsciint.2020.110612
L2 - https://doi.org/10.1016/j.forsciint.2020.110612
N2 - Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and verification. This paper proposes an approach using random forests, a machine learning method, to develop and test models for classification of legal age thresholds (15 years and 18 years) using 3D facial landmarks. Our approach was developed on a set of 3D facial scans from 394 Czech individuals (194 males and 200 females) aged between 10 and 25 years. The dataset was retrieved from a sizable database of Central European faces – The FIDENTIS 3D Face Database. Three main types of input variables were processed using random forests: I) shape (size-invariant) coordinates of 3D landmarks, II) size and shape coordinates of 3D landmarks, and III) inter-landmark distances, angles and indices. The performance rates for the combinations of variables and age threshold were expressed in terms of sensitivity and specificity. The overall accuracy rates varied from 71.4% to 91.5% (when the male and female samples were pooled). In general, higher accuracy was achieved for the age limit of 18 years than for 15 years. Whereas size-variant variables showed a better performance rate for the age limit of 15 years, the size-invariant variables (i.e., shape variables) were better for classifying individuals under 18 years. The verification models grounded on traditional variables (distances, angles, indices) yielded consistently higher performance rates on females than on males, whereas the inverse trend was observed for the models built on 3D coordinates. The results indicate that age verification based on 3D facial data with processing by the random forests method has high potential for further forensic or biometric applications.
ER -
JANDOVÁ, Marie, Marek DAŇKO a Petra URBANOVÁ. Age verification using random forests on facial 3D landmarks. \textit{Forensic Science International}. Clare: Elsevier Ireland Ltd, 2021, roč.~318, January, s.~1-10. ISSN~0379-0738. Dostupné z: https://dx.doi.org/10.1016/j.forsciint.2020.110612.
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